CMOS imagers are low cost imaging devices. A fully compatible CMOS sensor technology enabling a higher level of integration of an image array with associated processing circuits would be beneficial to many digital applications such as, for example, in cameras, scanners, machine vision systems, vehicle navigation systems, video telephones, computer input devices, surveillance systems, auto focus systems, star trackers, motion detection systems, image stabilization systems and data compression systems for high-definition television.
CMOS imagers have a low voltage operation and low power consumption; CMOS imagers are compatible with integrated on-chip electronics (control logic and timing, image processing, and signal conditioning such as A/D conversion); CMOS imagers allow random access to the image data; and CMOS imagers have lower fabrication costs as compared with, for example, the conventional CCD since standard CMOS processing techniques can be used. Additionally, low power consumption is achieved for CMOS imagers because only one row of pixels at a time needs to be active during the readout and there is no charge transfer (and associated switching) from pixel to pixel during image acquisition. On-chip integration of electronics is particularly advantageous because of the potential to perform many signal conditioning functions in the digital domain (versus analog signal processing) as well as to achieve a reduction in system size and cost.
In order to maintain the quality and brightness of an image at an optimal level, the exposure and gain settings have to be continually adjusted for varying light conditions. Exposure is the duration for which the pixel sensor is capturing photons and accumulating induced electrons. Gain is the amount of analog amplification or attenuation that a pixel sensor signal undergoes. Amplification is where the gain is greater than one and attenuation is where the gain is less than one.
By varying the exposure and the gain of a pixel sensor, optimal images can be obtained from a sensor. For example, for the bright light conditions of a beach on a sunny day, the exposure would be set to a minimum and the gain to less than or equal to one. Similarly, if the image desired to be captured is a polar bear in a snow storm, the exposure would be set to a minimum and the gain to less than or equal to one. For dark conditions such as when trying to capture an image of a deer at night, the exposure would be set to a maximum and the gain to greater than or equal to one. Automatic exposure and gain control algorithms, however, carry the risk of oscillations. If the desired exposure and gain and the actual exposure and gain do not converge, then oscillations result, which adversely impact the captured image.